| 1. |
- Brännström, Inger, 1945-
(författare)
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Community participation and social patterning in cardiovascular disease intervention
- 1993
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This study addresses health policy and public health in the field of cardiovascular disease (CVD) on the local level in Sweden. The overall aim is to contribute to the assessment of structural and social conditions within public health by analysing participation processes and outcome patterns in a local health programme. The northern Swedish MONICA study served as a reference area. The research strategy has been to integrate quantitative and qualitative methodologies and, thereby, focus on different aspects of the health programme under study.The mortality rate was excessive in the study area of Norsjö relative to both provincial and national figures over a period of more than 10 years. This finding formed the basis for a tenyear comprehensive and community-based health programme towards the prevention of CVD and diabetes.Even in this seemingly homogeneous area it was found that socio-economic circumstances were associated with the public health. Almost half of the study population had hypercholesterolaemia (;>6.5 mmol/1), 19% of men and 25% of women were smokers and 30% and 29%, respectively, had high blood pressure. Age had a strong impact on all outcome measures. After adjustments for age and social factors it was found that the relative risk of having hypercholesterolaemia dropped significantly in both sexes during the six years of intervention. The probability of being a smoker was significantly reduced only in highly educated groups. No statistically significant change over time could be found for the risk of suffering high blood pressure. In the reference area of northern Sweden there were no changes over time for any of the selected risk factors. The likelihood of self-assessed good health decreased with increasing risk factor load, with the exception of hypercholesterolaemia , in all social strata.The authorities, including the health and medical staff, were the main actors on the mediastage. Men in manual occupations were least affected by the media coverage. The actors and the public as well as the media viewed the health programme as orientated towards individual lifestyles. Community participation was mainly defined by the actors based on the medical and health planning approach. Differences in interpretations, social interests, personal conflicts and ideological constraints among the actors at local level were observed. Some critical attitudes towards the organization and management of the health programme were also noted among the citizens. However, a majority of the public wanted the health programme to continue. The present study underlines the importance of considering age, gender and social differences in the planning and evaluation of CVD preventive programmes.
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| 2. |
- Farooq, Zia, 1986-
(författare)
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Navigating epidemics : by leveraging data science and data-driven modelling
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Ours is an era of global change—including climate change, land-use change, urbanization, increased mobility of humans, species and goods, and environmental shifts. Concurrently, we are witnessing a tangible increase in the rate of (re)emerging infectious diseases, mostly driven by global change factors. This complex landscape of infectious diseases necessitates strategies underpinned by computational tools such as data-driven models to enhance our understanding, response, and predictions of potential epidemics.In this thesis, I leveraged data science algorithms and developed data-driven models that extend beyond specific pathogens, providing insights to prepare for future epidemics, with a focus on Europe. I delved into three temporal contexts: 1) retrospective analyses to understand the contribution of global change factors—specifically climate change and human mobility—fuelling the disease outbreaks and expansion (papers I & IV), 2) develop model to improve disease severity estimation during an outbreak for immediate response (paper III), and 3) future disease transmission risk trajectories under various projected scenarios of global change (paper II)—each playing a crucial role in proactive public health planning and response.In paper I, we assessed the predictive ability and the influence of eco-climatic factors on West Nile virus (WNV)—a pathogen with multiple hosts and mosqutio-vectors, and of public health concern in Europe. Utilizing an advanced machine learning classifier XGBoost, trained on a diverse dataset encompassing eco-climatic, sociodemographic predictors to the WNV presence/absence data, the model accurately predicted the WNV risk a season ahead. Furthermore, by employing an explainable AI algorithm, we uncovered both local and European-level drivers of WNV transmission. Higher temperatures in summer and spring, along with drier winters, were pivotal in the escalated frequency of WNV outbreaks in Europe from 2010 to 2019.In paper II, we projected the WNV risk under climate change and socioeconomics scenarios by integrating augmenting the outputs of climate ensemble into machine learning algorithms. We projected transmission risk trends and maps at local, national, regional and European scale. We predicted a three to five fold increase in WNV transmission risk during the next few decades (2040-60) compared 2000-2020 under extreme climate change scenarios. The proportion of diseasereported European land areas could increase from 15% to 23-30%, putting 161 to 244 million people at risk. Western Europe remains at largest relative risk of WNV increase under all scenarios, and Northern Europe under extreme scenarios. With the current rate of spread and in the absence of intervention or vaccines the virus will have sustained suitability even under low carbon emission scenarios in currently endemic European regions.In paper III, we developed a method to quantify an important epidemiological parameter-case fatality ratio (CFR)— commonly used measure to assess the disease severity during novel outbreaks. In our model, we accounted for the time lags between the reporting of a cases and that of the case fatalities and the probability distribution of time lags and derived the CFR and distribution parameters using an optimization algorithm. The method provided more accurate CFR estimations earlier than the widely used estimators under various simulation scenarios. The method also performed well on empirical COVID-19 data from 34 countries. In paper IV, we modelled annual dengue importations in Europe and the United States driven by human mobility and climate. Travel rates were modelled using a radiation model based on population density, geographic distance, and travel volumes. Dengue viraemic travellers were computed considering local mosquito bite risk, travel-associated bite probability, and visit duration. A dynamic vector life-stage model quantified the climatic suitability of transmissionpermissive local areas. Dengue importations linearly increased in Europe and the U.S. from 2015-2019, rising by 588% and 390%, respectively, compared to 1996-2000 estimates, driven by increased travel volumes (373%) and dengue incidence rates (30%) from endemic countries. Transmission seasons lengthened by 53% and 15% in Europe and the U.S., respectively, indicating increasingly permissive climates for local outbreaks. These findings apply to other diseases such as chikungunya, Zika, and yellow fever, sharing common intermediate host vectors, namely Aedes mosquitoes.This thesis highlights Europe's increasing vulnerability to infectious diseases due to global change factors, putting millions at risk. It emphasizes the significance of advanced modelling and innovative data streams in anticipating epidemic risks. Developing digital early warning systems to track disease drivers and taking urgent climate change mitigation and adaptation measures are crucial to anticipate and reduce future epidemic risks. The outcomes of this research can be used to develop technology-driven decision support tools to aid public health authorities and policymakers in making evidence-based decisions during and inter-epidemic periods.
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| 3. |
- Ghersheen, Samia, 1985-
(författare)
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Dynamics of Coinfection : Complexity and Implications
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Living beings are always on risk from multiple infectious agents in individual or in groups. Though multiple pathogens' interactions have widely been studied in epidemiology. Despite being well known, the co-existence of these pathogens and their coinfection remained a mystery to be uncovered. Coinfection is one of the important and interesting phenomenon in multiple interactions when two infectious agents coexist at a time in a host. The aim of this thesis is to understand the complete dynamics of coinfection and the role of different factors affecting these interactions.Mathematical modelling is one of the tools to study the coinfection dynamics. Each model has its own limitations and choice of the model depends on the questions to be addressed. There is always a crosstalk between the choice of model and limitation of their solvability. The complexity of the problem defines the restriction in analytical possibilities.In this thesis we formulate and analyse the mathematical models of coinfection with different level of complexities. Since viral infections are a major class of infectious diseases, in the first three papers we formulated a susceptible, infected, recovered (SIR) model for coinfection of the two viral strains in a single host population introducing carrying capacity as limited growth factor in susceptible class. In the first study, we made some assumptions for the transmission of coinfection in the model. In the following papers, the analysis is expanded by relaxing these assumptions which has generated the complexity in dynamics. We showed that the dynamics of stable equilibrium points depends on the fundamental parameters including carrying capacity K. A parameter dependent transition dynamics exists starting from disease free state to a level where coinfection can persists only with susceptible class. A disease-free equilibrium point is stable only when K is small. With increase in carrying capacity to a level where only single infection can invade and persists. Further increase in carrying capacity becomes large enough for the existence and persistence of coinfection due to the high density of susceptible class. In paper I, we proved the existence of a globally stable equilibrium point for any set of parameter values, revealing persistence of disease in a population. This shows a close relationship between the intensity of infection and carrying capacity as a crucial parameter of the population. So there is always a positive correlation between risk of infection and carrying capacity which leads to destabilization of the population.In paper IV, we formulated mathematical models using different assumptions and multiple level of complexities to capture the effect of additional phenomena such as partial cross immunity, density dependence in each class and a role of recovered population in the dynamics. We found the basic reproduction number for each model which is the threshold that describes the invasion of disease in population. The basic reproduction number in each model shows that the persistence of disease or strains depends on the carrying capacity K. In the first model of this paper, we have also shown the local stability analysis of the boundary equilibrium points and showed that the recovered population is not uniformly bounded with respect to K.Paper V uses simulations to analyse the dynamics and specifically studies how temporal variation in the carrying capacity of the population affects its dynamics. The degree of autocorrelation in variability of carrying capacity influences whether the different classes exhibit temporal variation or not. The fact that the different classes respond differently to the variation depends in itself on whether their equilibrium densities show a dependence on the carrying capacity or not. An important result is that at high autocorrelation, the healthy part of the population is not affected by the external variation and at the same time the infected part of the population exhibits high variation. A transition to lower autocorrelation, more randomness, means that the healthy population varies over time and the size of the infected population decreases in variation.
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| 4. |
- Liu-Helmersson, Jing, 1960-
(författare)
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Climate Change, Dengue and Aedes Mosquitoes : Past Trends and Future Scenarios
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Background Climate change, global travel and trade have facilitated the spread of Aedes mosquitoes and have consequently enabled the diseases they transmit (dengue fever, Chikungunya, Zika and yellow fever) to emerge and re-emerge in uninfected areas. Large dengue outbreaks occurred in Athens in 1927 and in Portuguese island, Madeira in 2012, but there are almost no recent reports of Aedes aegypti, the principal vector, in Europe. A dengue outbreak needs four conditions: sufficient susceptible humans, abundant Aedes vector, dengue virus introduction, and conducive climate. Can Aedes aegypti establish themselves again in Europe in the near future if they are introduced? How do the current and future climate affect dengue transmission globally, and regionally as in Europe? This thesis tries to answer these questions.Methods Two process-based mathematical models were developed in this thesis. Model 1 describes a vector’s ability to transmit dengue – vectorial capacity – based on temperature and diurnal temperature range (DTR). Model 2 describes vector population dynamics based on the lifecycle of Aedes aegypti. From this model, vector abundance was estimated using both climate as a single driver, and climate together with human population and GDP as multiple drivers; vector population growth rate was derived as a threshold condition to estimate the vector’s invasion to a new place.Results Using vectorial capacity, we estimate dengue epidemic potential globally for Aedes aegypti and in Europe for Aedes aegypti and Aedes albopictus. We show that mean temperature and DTR are both important in modelling dengue transmission, especially in a temperate climate zone like Europe. Currently, South Europe is over the threshold for dengue epidemics if sufficient dengue vectors are present. Aedes aegypti is on the borderline of invasion into the southern tip of Europe. However, by end of this century, the invasion of Aedes aegypti may reach as far north as the middle of Europe under the business-as-usual climate scenario. Or it may be restricted to the south Europe from the middle of the century if the low carbon emission – Paris Agreement – is implemented to limit global warming to below 2°C.Conclusion Climate change will increase the area and time window for Aedes aegypti’s invasion and consequently the dengue epidemic potential globally, and in Europe in particular. Successfully achieving the Paris Agreement would considerably change the future risk scenario of a highly competent vector – Aedes aegypti’s – invasion into Europe. Therefore, the risk of transmission of dengue and other infectious diseases to the mainland of Europe depends largely on human efforts to mitigate climate change.
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| 5. |
- Andersson, Bea Angelica, 1992-
(författare)
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Finding fitness : empirical and theoretical explorations of inferring fitness effects from population-level SNP data
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The distribution of fitness effects (DFE) describes the likelihood that a new mutation has a specific effect on the fitness of an individual in a given population. The shape of the DFE is a result of several factors such as population size, mating system and selective environment, and can in turn influence the evolutionary potential of a species. The DFE has long been a field of intense research, but particularly since molecular methods enabled us to study of genetic variation in organisms empirically. This research has led to the development of several statistical methods that use population-level frequencies of single nucleotide polymorphisms (SNPs) to infer the DFE. However, these methods rely on assumptions about the data and the organism itself, which could potentially affect the accuracy of the inferences. In this thesis, I describe how two major factors – data quality and inbreeding – can affect the accuracy of DFE inferences. I also show how and when to (and when not to) use DFE inference methods based on SNP frequencies.All genomic datasets contain inaccuracies and some level of uncertainty. The data sets are therefore often treated to remove the gaps or less reliable information, such as genotypes with low coverage. Some data sets need heavy filtering, which could reduce the amount of data available for analysis. We show that the choice of filter method affects the size of the final data set and the accuracy of the estimated DFE.Many DFE estimation software assumes random mating within the study population. Unfortunately, this assumption induces some error when trying to estimate the DFE in inbred or selfing species. Some have assumed that this is a result of high rates of homozygosity in the data, and should only be a problem in populations with very high rates of selfing (>99%). We show that accuracy of the estimated DFE decreases already at relatively low rates of selfing (70%) and that removing homozygosity does not improve the accuracy, implying that another mechanism could be causing the error.
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| 6. |
- Fransson, Peter, 1988-
(författare)
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Optimal thinning : a theoretical investigation on individual-tree level
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Paper I: In paper I, we asked how a tree should optimally allocate its resources to maximize its fitness. We let a subject tree grow in an environment shaded by nearby competing trees. The competitors were assumed to have reached maturity and had stopped growing, thus creating a static light environment for the subject tree to grow in. The light environment was modeled as a logistic function. For the growth model we used the pipe model as a foundation, linking tree width and leaf mass. This allowed us to construct a dynamic tree-growth model where the tree can allocate biomass from photosynthesis (net productivity) to either stem-height growth, crown-size growth, or reproduction (seed production). Using Pontryagin's maximum principle we derived necessary conditions for optimal biomass allocation, and on that built a heuristic allocation model. The heuristic model states that the tree should first invest into crown-size and then switch to tree height-growth, and lastly invest into crown-size before the growth investments stop and all investments are allocated to reproduction. To test our heuristic method, we used it to determine the growth in several different light environments. The results were then compared to the optimal growth trajectories. The optimal growth was determined by applying dynamic programming. Our less computationally demanding heuristic performed very well in comparison. We also found there exist a critical crown-size: if the subject tree possessed a larger crown-size, the tree would be unable to reach up to the canopy height.Paper II: One of the most important aspects of modelling forest growth, and modelling growth of individual trees in general, is the competition between trees. A high level of competition pressure has a negative impact on the growth of individual trees. There are many ways of modelling competition, the most common one is by using a competition index. In this paper we tested 16 competition indices, in conjunction with a log-linear growth model, in terms of the mean squared error and the coefficient of determination. 5 competition indices are distance-independent (i.e. distance between the competitors are not taken into consideration) and 11 are distance-dependent. The data we used to fit our growth model, with accompanying competition index, was taken from an experimental site, in northern Sweden, of Norway spruce. The growth data for the Norway spruce comes from stands which were treated with one of two treatments, solid fertilization, liquid fertilization, or no treatment (control stand). We found that the distance-dependent indices perform better than the distance-independent. However, both the best distance-dependent and independent index performed overall well. We also found that the ranking of the indices was unaffected by the stand treatment, i.e. indices that work well for one treatment will work well for the others.Paper III: In this paper we studied how spatial distribution and size selection affect the residual trees, after a thinning operation, in terms of merchantable wood production and stand economy. We constructed a spatially explicit individual-based forest-growth model and fitted and validated the model against empirical data for Norway spruce stands in northern Sweden. To determine the cost for the forest operation we employed empirical cost functions for harvesting and forwarding. The income from the harvested timber is calculated from volume-price lists. The thinnings were determined by three parameters: the spatial evenness of residual trees, the size selection of removed trees, and the basal area reduction. In order to find tree selections fulfilling these constraints we used the metropolis algorithm. We varied these three constrains and applied them for thinning of different initial configurations of Norway spruce stands. The initial configurations for the stands where collected from empirical data. We found that changing the spatial evenness and size selection improved the net wood production and net present value of the stand up to 8%. However, the magnitude of improvement was dependent on the initial configuration (the magnitude of improvement varied between 1.7%—8%).Paper IV: With new technology and methods from remote sensing, such as LIDAR, becoming more prevalent in forestry, the ability to assess information on a detailed scale has become more available. Measurements for each individual tree can be more easily gathered on a larger scale. This type of data opens up for using individual-based model for practical precision forestry planning. In paper IV we used the individual-based model constructed in paper III to find the optimal harvesting time for each individual tree, such that the land expectation value is maximized. We employed a genetic algorithm to find a near optimal solution to our optimization. We optimized a number of initial Norway spruce stands (data obtained from field measurements). The optimal management strategy was to apply thinning from above. We also found that increasing the discount rate will decrease the time for final felling and increase basal area reduction for the optimal strategy. Decreasing relocation costs (the cost to bring machines to the stand) led to an increase in the number of optimal thinnings and postponed the first thinning. Our strategy was superior to both the unthinned strategy and a conventional thinning strategy, both in terms of land expectation value (>20% higher) and merchantable wood production.
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| 7. |
- Sjödin, Henrik, 1975-
(författare)
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Population-level consequences of spatial interactions
- 2013
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- How is the nature of populations governed by the movement decisions made by their members? This is the core question in this thesis. To answer this question, I first assume that s movement decisions are based on conditions in their local environment. Then I derive mathematical relationships that distil the character of individual movement events, and relate the sum of these events to the dynamical properties of the population. I find that the fate of populations depend delicately on the way resident individuals relocate in response to local conditions. This general conclusion is supported by results in the four papers constituting this thesis.In the first paper we derive a deterministic approximation of a stochastic individual-based spatial predator-prey model. We show how general types of movement behaviors either stabilise or destabilise predator-prey dynamics. Based on experimental data on movement behaviors, we conclude that predator-prey dynamics are stabilised if the prey species respond stronger to predator presence than the predatory species respond to prey.In the second paper we derive a new type of functional response that arise when there is a behavioral spatial “race” between predators and prey. Although fundamentally different from classical functional responses, the induced density-dependencies in reproduction rates are similar to those in Holling’s type II and DeAngelis-Beddington’s functional responses.In the third paper we perform a novel systematic investigation of density-dependencies in population growth-rates induced by the spatial covariance in empirical predator-prey systems. We categorise three types of density dependencies: “lagged”, “direct” and “independent”, and find direct and especially lagged density-dependencies to be common. We find that the density-dependencies in most cases are destabilising, which is at odds with the wide-spread view that spatial heterogeneity stabilises consumer-resource dynamics. We also find dependencies of prey density to be more common than of predator density.In the forth paper we consider the evolution of cooperation. We formulate a stochastic individual-based group-formation process and show that profit-dependent group disengagement is evolutionarily stable and allows the emergence of stable cooperative communities.
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| 8. |
- Wickman, Jonas, 1985-
(författare)
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Evolution of Ecological Communities in Spatially Heterogeneous Environments
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Evolutionarily stable communities are the endpoints of evolution, and ecological communities whose traits are under selection will eventually settle into them. Hence, the properties of such communities are of particular interest, as they can persist over long evolutionary time scales. The notion of an evolutionarily stable strategy - an evolved strategy that cannot be beat by any other once established - has now been part of theoretical ecology for almost 50 years, and the theory for evolutionarily stable strategies and communities, and how they are reached has become increasingly versatile. However, for environments where conditions vary in space, so-called heterogeneous environments, efficient analytical and numerical tools for studying evolutionarily stable communities and how they come about have been lacking. Hence, many questions regarding how evolutionarily stable diversity is generated and maintained when ecological and evolutionary forces vary in space remain unexplored. In particular, how spatially averaged selection and selective forces derived from spatial variability can act together to either promote or inhibit evolutionarily stable diversity is not well understood. In this thesis, I use a two-pronged approach towards answering such questions by developing the necessary analytical and numerical tools for assembling and analyzing evolutionarily stable communities in heterogeneous environments, and by then employing these tools to study communities of resource competitors and food webs. Specifically, I derive expressions for directional and stabilizing/disruptive selection when the spatially heterogeneous ecological dynamics of a community are described by reaction-diffusion equations. These expressions allow us to understand selection across an environment in terms of local selection pressures, and also enable efficient numerical implementations of evolutionary community assembly procedures that lead to evolutionarily stable communities. Applied to the communities of resource competitors and food webs I find that the selective forces derived from spatially averaged selection and those derived from spatial variability can act both in concert or in opposition. If these forces act in opposition and if the spatial variability of local selection is high, a high diversity of organisms can form even when spatially averaged selection is stabilizing. In contrast, if spatially averaged selection is disruptive, it can prevent more diverse communities from forming by creating few globally unbeatable strategies. However, these forces can also act disruptively in concert to create more diverse communities. Together, these results demonstrate a surprising variety of qualitatively different outcomes when evolutionarily stable communities are assembled in heterogeneous environments.
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| 9. |
- Brännström, Lars, 1972-
(författare)
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Phantom of the Neighbourhood : Longitudinal Studies on Area-based Conditions and Individual Outcomes
- 2006
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This dissertation consists of three self-contained but interrelated empirical studies focusing on theoretical, empirical and political questions in the multidisciplinary field of neighbourhood effect research. Along with a comprehensive introductory essay, each study addresses questions concerning the potential influence of neighbourhood characteristics on individual social and economic outcomes at different life stages. Study I combines longitudinal register and survey data from the ‘golden era’ of Swedish welfare policy to evaluate a hypothesised impact of neighbourhood poverty during adolescence on a wide range of outcomes (including, but not limited to, educational and employment status) within a counterfactual model framework based on matching on propensity scores. Extensive empirical analyses indicate that, when two groups of children who are identical according to observed factors before age 10 (including household income, family structure and welfare receipt) live in different types of neighbourhood in adolescence, the outcome for those who grow up in a poor neighbourhood is not more likely to be worse than for those who grow up in a more affluent neighbourhood. Study II considers the maximum theoretical scope of unique neighbourhood influence experienced during the years of growth on individuals’ later life income and social assistance recipiency. A three-level hierarchical linear model is applied to simultaneously distinguish variation in the outcomes over time from variation that is attributable to differences between neighbourhoods. By utilising longitudinal register data derived from a birth cohort who grew up in Stockholm at a time when Swedish welfare policy ambitions were at a peak, this study attempts to estimate the long-term significance of neighbourhood origin in the Swedish setting. The analyses clearly show that prior place of residence accounts for an exceedingly modest proportion of the variation in cohort members’ subsequent income and receipt of social assistance. Study III explores the hypothesised negative impact of disadvantaged neighbourhood conditions, individual disadvantage, and degree of labour market establishment on levels of social trust. Using data from the Swedish Longitudinal Survey among Unemployed, ordered logit regression analyses indicate that low levels of social trust are contingent upon perceived neighbourhood disorder, personal powerlessness, perceived fear of victimisation, and accumulated episodes of temporary employment. The tentative results also indicate that neighbourhood disorder, powerlessness, and fear of victimisation interact, magnifying the negative impact on social trust.
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| 10. |
- Isaksson, Hanna, 1995-
(författare)
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Adaptation during the early evolution of multicellularity : mathematical models reveal the impact of unicellular history, environmental stress, and life cycles
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Multicellular organisms, such as plants and animals, have independently evolved several times over the last hundreds of millions of years. The evolution of multicellularity has significantly shaped modern ecosystems, yet its origins remain largely unknown. Due to the ancient history and the small size scale of early multicellular organisms, few intact fossils have been preserved. To uncover the origins of large and complex life, researchers have turned to alternative methods such as phylogenetic modeling, experimental evolution, and theoretical frameworks. While these approaches have provided novel insights in the early steps of multicellular evolution, few studies have considered the role of adaptation in these novel life cycles. This thesis addresses the gap in our knowledge by employing mathematical modeling and computer simulations to study adaptation in novel multicellular life cycles.The first paper investigates the effects of unicellular reproduction modes, such as budding or binary fission, on the spread of growth rate mutations. It demonstrates that unicellular history significantly influences the adaptation rate, with budding cells exhibiting greater sensitivity to the spatial distribution of mutations.In Paper II, the role of multicellular reproduction mode for the adaptation of altruistic and selfish mutations is explored. Specifically, the study examines how adaptation is affected when the filaments are exposed to a size-based selective pressure. It reveals that while the adaptation of altruistic mutations is favored by large offspring, the spread of selfish mutations depends on both offspring size and selection strength.While Papers I and II assume deterministic life cycle structures at the multicellular level, paper III investigates the evolution of life cycle regulation when cells use internal information. The model demonstrates that when cells only have access to a limited amount of information, there is significant variation in the types of life cycles that emerge. This suggests that to evolve regulated life cycles, additional mechanisms beyond internal information may be necessary, such as cell communication.Papers I-III explore multicellular life cycles where all cells are of the same type, yet most multicellular organisms have evolved cell differentiation, with specialized cells performing various tasks. In Paper IV, the evolutionary paths leading to differentiated multicellularity are investigated when a unicellular population is exposed to an abiotic (non-evolving) selective pressure. The model reveals that while a wide range of phenotypic backgrounds and environmental conditions may induce differentiation and multicellularity, continued adaptation to the stress eventually leads to reversion to unicellularity. This reversion occurs because as cells adapt to the stress, the costs associated with differentiation and group formation may no longer be justified. One potential strategy to prevent reversion could involve considering biotic selective pressures that can co-evolve with the population.Lastly, paper V delves into organisms composed by combinations of uni- and multicellular species. Utilizing this framework to examine present multi-species multicellularity reveals that the species composition influences both the ease of partnership establishment and its stability. Additionally, these chimeric groups can reproduce through various strategies, including fragmentation and complete dissociation. Leaving the constellation endows organisms with a memory of prior partnerships, enhancing their adaptability in forming new ones. This extension opens up novel evolutionary pathways for further exploration.In summary, this thesis offers new insights into how the life cycle structures of simple multicellular organisms impact mutation accumulation and the acquisition of new traits. The adaptability of organisms plays a pivotal role in fostering higher complexity and paving the way for further evolution. Enhancing our understanding in this domain will continue to illuminate the origins of complex life and elucidate the evolutionary factors underlying the rich diversity of multicellular organisms we encounter today.
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